If you want to make money online : Register now

Effect of value of k in K-Nearest Neighbor

, , No Comments
Problem Detail: 

In K-Nearest Neighbor the value of k decides the accuracy of classification. What are the pros and cons of choosing smaller value for k and larger value for k?

Asked By : Daga
Answered By : D.W.

There is no simple answer. The standard approach to choose $k$ is to try different values of $k$ and see which provides the best accuracy on your particular data set (using cross-validation or hold-out sets, i.e., a training-validation-test set split).

Intuitively, $k$-nearest neighbors tries to approximate a locally smooth function; larger values of $k$ provide more "smoothing", which or might not be desirable.

Best Answer from StackOverflow

Question Source : http://cs.stackexchange.com/questions/49792

3200 people like this

 Download Related Notes/Documents


Post a Comment

Let us know your responses and feedback